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Job Title


Associate Data Scientist - GenAI


Company : Manulife Financial


Location : Toronto, Ontario


Created : 2026-01-26


Job Type : Full Time


Job Description

We are seeking a highly skilled and motivated Associate Data Scientist to join our team. You will be responsible for developing and implementing AI and Machine Learning models, using Generative AI techniques, such as applying prompt engineering, working with RAG applications, fine-tuning LLM models, and deploying applications on cloud platforms like Azure. Your expertise in these areas will play a crucial role in driving data-driven decision-making and enhancing our business processes. Position Responsibilities Develop and implement AI models to solve complex business problems, using a variety of algorithms and techniques. Clean, preprocess, and analyze large datasets to extract meaningful insights and patterns. Apply prompt engineering techniques, build with RAG (Retrieval-Augmented Generation) applications, and fine-tune language models and improve their performance in specific tasks. Collaborate with multi-functional teams to identify and define business requirements, ensuring alignment with data science objectives. Apply generative AI techniques to generate synthetic data, create realistic simulations, and enhance data analysis capabilities. Design and complete experiments to validate and optimize machine learning models, ensuring accuracy, efficiency, and scalability. Deploy machine learning models and applications on cloud platforms like Azure ML or Databricks, ensuring seamless integration and scalability. Stay up-to-date with the latest advancements in machine learning, generative AI, prompt engineering, RAG applications, and cloud technologies, and apply them to enhance our data science capabilities. Collaborate with data engineers and ML engineers to integrate data science solutions into existing systems and workflows. Communicate complex technical concepts and findings to both technical and non-technical partners, ensuring clear understanding and agreement. Required Qualifications Bachelor, Master''''s degree, or Ph.D. in Computer Science, Data Science, Statistics, or a related field. Proven experience as a Data Scientist including internships or coops, with a strong focus on machine learning, generative AI, prompt engineering, and RAG applications. Solid understanding of machine learning algorithms, statistical modeling, and data analysis techniques. Proficiency in programming languages such as Python and experience with machine learning libraries/frameworks (e.g., PyTorch, scikit-learn, Hugging Face). Preferred Qualifications Strong problem-solving skills and the ability to think critically and creatively to develop innovative solutions. Excellent communication and collaboration skills, with the ability to work effectively in multi-functional teams. When you join our team Well empower you to learn and grow the career you want. Well recognize and support you in a flexible environment where well-being and inclusion are more than just words. As part of our global team, well support you in shaping the future you want to see. https://www.manulifeim.com/institutional/tw/en [email protected] Referenced Salary Location Toronto, Ontario Working Arrangement Salary range is expected to be between $69,525.00 CAD - $115,875.00 CAD Manulife offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in Canada includes holidays, vacation, personal, and sick days, and we offer the full range of statutory leaves of absence. If you are applying for this role in the U.S., please contact [email protected] for more information about U.S.-specific paid time off provisions. #J-18808-Ljbffr